Deadline-aware caching using echo state network integrated fuzzy logic for mobile edge networks

Abstract

The rapid growth of wireless data has caused cellular networks (3G/LTE/4G) to be overburdened, which affects the user’s quality of experience. In a mobile edge computing (MEC) architecture, caching the content at the base stations cooperatively is a prudent solution and this reduces the user-perceived latency as it brings the content closer to the user and minimizes the burden on the backhaul. However, to enhance the quality of service in delay-sensitive and time-critical applications, the requested content should be served within the deadline. Therefore, maximizing the storage utilization while maximizing the saved delay in the mobile edge network is a critical problem. To address these challenges, in this paper, we formulate a cache placement problem in mobile edge networks as placing the contents at different MECs (base stations) to maximize the saved delay with capacity and deadline constraints. The problem is modeled as an integer linear programming problem for content placement in mobile edge network. A relaxation and rounding method is presented to solve the integer linear programming problem. Further, we propose a fuzzy logic based caching algorithm that considers deadline, benefit and content request prediction in caching decisions. In the proposed algorithm, the echo state network is used to predict content request distribution. Extensive simulation results show that the proposed fuzzy caching scheme significantly improves the performance in terms of acceleration ratio, hit ratio and the number of files satisfying deadline on MovieLens dataset as compared with three existing caching techniques.